McDowd, Joan M. PhD
William James's1 comment that “everyone knows what attention is” is often quoted to illustrate the difficulty of precisely defining attention, resorting rather to the truism that everyone knows what it is. However, James had much more to say on the topic; following the declaration above, he goes on to say that attention “is the taking possession by the mind, in clear and vivid form, of one of what seem several simultaneously possible objects or trains of thought. Focalization, concentration of consciousness are of its essence.”
Concentration, or focalization, is indeed a core concept in understanding attention. Control of attention allows us to choose what information from our environment will be processed and to block out information that is not relevant to the task at hand. Control of attention allows us to behave efficiently, although there is a cost associated with this ability. Paying attention to one thing necessarily means we are not processing other things; our capacity to attend is limited. The extent of these limits differs as a function of chronological age, neurological status, fatigue, stress, practice, and other factors. Understanding how attention typically operates is the first step in understanding how it may be altered by other factors and how deficits may be ameliorated to improve the efficiency of behavior.
The purpose of this article is to provide an overview of attention as it has been studied in the field of psychology. The amount of research devoted to understanding attention is huge, and it is well beyond the scope of this paper to touch on all this work or the associated theoretical developments. Instead, I have chosen to highlight broad themes in terms of theory and to take a functional approach to understanding attention, decomposing it in terms of the task contexts in which it may operate. The goal is to provide a foundation that would allow readers to then pursue specific areas of interest on their own.
METAPHORS OF ATTENTION
The Attentional Spotlight
Perhaps the most common metaphor for the functioning of attention is the spotlight.2–5 The spotlight beam stands for the focus of attention, and cognitive processing is most efficient for information that falls within that spotlight. Information outside of the spotlight can be processed only superficially if at all. Thus, the spotlight of attention “lights up” the most relevant information for the task at hand, making it readily available for processing by the cognitive system. In this metaphor, there is generally only one focus for processing at any given point in time.
A second metaphor for attention involves the notion of a pool or reservoir of attention that can be allocated to multiple processing tasks as long as the allocation does not exceed the amount of available resources.6 The individual controls the allocation of attention to goal relevant information; information not receiving an allocation of attention is not processed. However, in this model, multiple streams of information can be performed simultaneously as long as they are fairly easy and their processing does not require more attentional resources than are available. If processing does require more resources than are available, two outcomes are possible. The first is that task performance will suffer; the second is that tasks will have to be prioritized and performed sequentially so as not to exceed available resources.
The concept of resources has been more than a metaphor in the development of research on attention. Empirical work has demonstrated that different people may have different amounts of attentional resources available to them, depending on age, health, or experience. Factors such as stress,7 anxiety, and fatigue8 may temporarily reduce the attentional resources a person has. Different tasks require different amounts of resources, and practice can reduce the amount of resources required by a task.
Although popular due to its intuitive appeal, the concept of attentional resources has been criticized in the literature.9,10 One primary sticking point has been the definition of what resources are exactly; without a precise definition, it is difficult to know how they might be measured. Even so, the concept continues to be used in empirical and theoretical work today to describe differences between populations (eg, young versus old adults)11 or clinical conditions (eg, healthy adults versus stroke survivors).12
Related to the concept of resources is the notion of attentional effort. The experience of paying more attention when confronted with a challenging task is fairly common. For example, if we find ourselves trying to have a conversation in a noisy environment over which we have no control, we may require additional attentional effort to understand the speaker's message. If we are confronted with a difficult or unfamiliar task, bringing additional attentional effort to bear on task performance may be essential for successful performance. Although these examples may be readily recognizable, the theoretical and empirical challenge has been to specify what it means to apply additional effort to a task.
Recent work by Sarter et al13 described a model involving both psychological and brain functions to explain attentional effort. In the examples above, a reasonable inference would be that attentional effort is modulated by task difficulty. In the Sarter et al view, increased attentional effort results from a person's motivation to perform well in the face of task challenges. This is a “top-down” view of attentional effort, meaning that effort is a result of a person's goals, intentions, and motivation rather than a product of specific task characteristics. Thus, attentional effort is an active and controlled process and, in the Sarter et al model, is mediated by cortical, mesolimbic, and cholinergic systems. These brain systems contribute to increasing the efficiency of processing incoming information, strengthening the filtering of irrelevant information, and ensuring that processing activities focus on the most relevant information. Sarter et al cite a significant amount of literature that is consistent with their model, representing significant progress toward translating the metaphors of attentional processes into observable brain activity.
INTERNAL AND EXTERNAL CONTROL OF ATTENTION
The metaphors that describe attention as a spotlight or a reservoir of resource are useful heuristics for illustrating attentional phenomena and thinking about the way attention works in human cognition. Like any metaphor or model, however, each makes some unstated assumptions about how attention works. For example, these metaphors emphasize the individual's active internal control of the focus of attention. However, there are also situations in which attention is directed at one thing, and an external event “grabs” attention away to something else.14,15 For example, you may be stopped at a traffic light in your car, listening intently to a radio news story of interest. All your attention is focused on the story, and you do not attend to the traffic light until another driver honks to indicate that the light has turned green. The honk got your attention in a way that you did not specifically control, indicating that a significant external stimulus is capable of capturing your attention. Once you have responded appropriately to the external stimulus, you can redirect your attention to the task of driving and listening to the radio. One of the most important aspects of efficient behavior is maintaining an appropriate balance between the internal and external control of attention. Generally, efficient behavior requires that individuals maintain control of the direction and focus of their attention.16 However, this control should not be absolute, as important external signals may occur outside of an individual's current focus of attention. At the same time, efficient behavior is not possible when attention is continually redirected by the occurrence of external events. Thus, there is a need to achieve a balance between the internal or external control of attention.
ATTENTION BEHAVIOR: A TAXONOMY OF TASK CONTEXTS
The fundamental role of attention is to focus the cognitive processing system on a subset of available information. Optimal performance results when the focus is on task-relevant information, at the expense of processing less relevant or irrelevant information. This optimization of performance occurs in different task contexts, which have been described as selective attention, divided attention, sustained attention, and switching attention. Each of these task contexts involves are considered here.
When the task context requires selective attention, the individual is focusing on just one source of information for processing and not processing other sources of information available in the environment. For example, if you are reading a good book in an airport waiting area, you are not listening to the conversations of people around you or watching the people hurrying along the concourse. The information outside of your focus is not processed and you may not even be aware of it.
Maintaining the momentary focus of attention is effortful and is not always successful. Failures of selective attention result in distraction, which in the best case merely reduces behavioral efficiency and in the worse case results in serious threats to personal safety. Being distracted while reading can increase the amount of time it takes to complete the reading tasks and may also reduce comprehension. Being distracted while driving, for example, can lead to much more serious outcomes.
Researchers interested in selective attention have generally measured the control of selection by presenting tasks that involve multiple stimuli, some that are relevant and some that are not. The individual attempts to perform a task involving just the relevant information and to ignore the irrelevant information. A variety of task parameters that enhance or interfere with selective processing have been identified. For example, in a visual selective attention task where the subject has to selectively attend to a target T that is upright or upside down, the target is much more quickly located and attended if it is surrounded by a field of Os than if it is surrounded by a field of upright and upside down Ls. Thu, target/distracter similarity is an important variable in determining the ease of selection.17–19
Another important variable is the predictability of target location. If a target is always presented in the same location or if the upcoming target location is cued, then its selection and identification can happen more quickly and the presence of distracters is less disruptive than if location is not known ahead of time.20,21 The spatial focus of attention, or knowing where to focus attention, is critical to efficient speeded behavior. This has been shown to be true for both visual information and auditory information.
The temporal predictability of distracter information is also important in determining the ease of maintaining the focus of attention on target information. In both the visual and auditory modality, if distracting information is presented at random or unpredictable intervals, it is more likely to capture attention than if it can be anticipated at regular, predictable intervals.22 Web-based advertisers capitalize on this aspect of attention when they design “pop-up” boxes to grab your attention at unpredictable times. These pop-ups are very difficult to ignore, and you nearly always have to look at them and take some action such as clicking on them in order to refocus your attention on whatever target information you were attending to previously.
Another aspect of selective attention that has interested researchers is the question of how distracting information is kept out of the focus of attention. On the one hand, distracting information may not reach awareness simply because it did not receive the facilitative benefit of attention. On the other hand, some models of selective attention involve both facilitative and inhibitory components for accomplishing selection. In these models, selective attention is accomplished not only by active processing of target information, but also active inhibition or suppression of distracting information.23 Deficits in selective attention performance may then be explained by either a failure in facilitative processing of target information or a failure in the inhibition of distracting information. Understanding selective attention in terms of facilitation and inhibition may increase the precision with which we can identify problems with selection in various populations. For example, it has been suggested that inhibitory processes are compromised in aging and in clinical populations such as people with schizophrenia or people with obsessive-compulsive disorder. Although the data are not unequivocal on these groups, identifying the source of attention deficits is the first step in developing approaches to ameliorate such deficits.
Attention is said to be divided whenever an individual is processing more than one source of information at a time or performing more than one task at a time. Many of the same principles associated with selective attention also apply in situations of divided attention, except that there are multiple foci for attentional processing.
People are remarkably adept at performing more than one task at a time. We converse while driving a car, knit while watching TV, prepare a meal while thinking about the events of the day, and so forth. In many cases, two tasks can be performed at once with little or no decrement in performance relative to conditions when the tasks are each performed separately. However, if the tasks are difficult and approach the limits of available capacity, performance on one or both tasks may decline. This decline is frequently referred to as the divided-attention deficit, or dual-task deficit.
Capacity models of attention were developed largely to understand and explain divided attention performance. The models incorporate the metaphor of attentional resources, reflecting the fact that the terms capacity and resources are often used interchangeably. There are two primary categories of capacity models: those that posit a single, undifferentiated attentional resource and those that propose multiple, independent attentional resources. Kahneman's6 initial model involved an undifferentiated resource. However, this model could not explain why some task combinations were easier than others or why some difficult tasks could be performed together without any problem at all. Further theoretical developments for capacity models led to models such as Wickens' multiple resource model.24 In that model, resources are multidimensional. Wickens proposed four resource dimensions: modality (auditory, visual), processing stage (encoding, central processing, responding), information code (spatial, verbal), and response mode (manual, vocal). In this theory, tasks performed simultaneously in a divided attention situation will interfere with one another to the extent that each task draws on the same resources as the other. Conversely, if two tasks involve different resource dimensions, then those tasks should be performed simultaneously with little difficulty.
Empirical findings25–27 have generally supported Wickens' model, although the processing domains required by tasks are not perfect predictors of performance. Other factors that affect divided attention performance include individual variables such as fatigue, which tends to increase the dual-task deficit, and familiarity with the two tasks, which tends to decrease the magnitude of the dual-task deficit. Practice with the individual tasks and with performing them simultaneously can also reduce the magnitude of the dual-task deficit. Often even if tasks require separate resources, there is a concurrence cost of performing them together.28,29 That is, the process of coordinating and executing two tasks at once is itself a resource-demanding task and may produce some dual-task deficit.
Driving an automobile is one of the most complex divided-attention tasks that people perform. Those of us who have learned to drive could each attest to the contribution of practice to the efficiency of divided attention performance; what starts out as an incredibly complex task involving multiple components becomes almost second nature, even though task requirements themselves have not changed. In terms of resource theory, repeated practice with two tasks allows performance to become more automatic by becoming more familiar, more efficient, and less demanding of resources. After sufficient experience with complex tasks, they no longer require all available resources to perform; they become nearly automatic and free up resources for other tasks.
Attention switching describes the task context in which a person alternates the focus of attention between two different tasks or sources of information. Performance may look similar to divided attention, but the assumptions about the underlying attentional processes are different. In divided attention, the assumption is that attention is shared between multiple sources of information. In attention switching, only one source of information is attended at any given moment in time, but the focus of attention may rapidly switch back and forth between multiple sources.30
Attention switching may be an option when truly simultaneous performance is not possible, either because of overlapping resource requirements or task difficulty that exceeds available resources. For example, driving a car requires the visual monitoring of multiple sources of information, primarily the instrument panel on the dashboard and the external environment. However, our visual information processing system makes it impossible to look at two places at the same time, so attention must be switched between the instruments on the dashboard and the street or surrounding environment. Engineers are working on the most efficient ways to design cars to allow easy monitoring of both sources of information and have come up with a design feature called “heads up display.” With heads up display, information from the dashboard can be projected onto the lower part of the car's windshield so the driver can alternate attention between the instruments and the road without moving the head. Attention still has to be switched in depth from the near windshield to the far road, but it can be accomplished without entirely taking one's eyes off the road. This design thus facilitates necessary attention switching while reducing threats to safety in the vehicle. Similar designs are being developed for airplane pilots whose instrument monitoring tasks are even more complex.31
Although it may seem as though switching would always be more efficient than dividing attention, that is not necessarily the case. Switching incurs its own sort of concurrence costs.32–34 Generally, the switching costs come in the form of additional demands on memory. Switching from one task to another requires that the individual remember the status of one task while performing the other, so that when attention is switched back to the first task, it can be resumed with minimal loss of efficiency. Switching also requires a resetting of task priorities with each switch; an individual's mental set has to switch from the requirements of one task to the requirements of the second task and back again. These switching costs typically result in slower or more error prone performance, especially immediately following a switch.
Maintaining attention to a task over prolonged periods of time is called sustained attention. Performing in this task context is hopefully very efficient in security guards, air traffic controllers, and the like. Sustained attention, also referred to as vigilance, can be described as selective attention maintained over time. Maintaining concentration over time is effortful and requires good control of attention so that distracting thoughts or environmental events do not capture attention away from its focus.
Experimentally, sustained attention is typically measured by having people monitor a long stream of rapidly presented information for the occurrence of a rare target. If attention wanders even for a short period of time, it is likely that target information will missed. The likelihood of missing target information increases with time on task, as the difficulty of sustaining attention increases over time. This reduced efficiency of sustained attention over time is called the vigilance decrement.35
As with other modes of attention, the efficiency of sustained attention is affected by fatigue and stress, among other factors. Some of these other factors include the frequency with which target information is presented and the predictability of target location. For example, Mouloua and Parasuraman36 found that vigilance decrements were greater when the frequency of target presentation was rare and when there was uncertainty about the location in which the targets would be presented. Both of these manipulations of task parameters make it more likely that a wandering of attention would lead to an increased probability of missing a target. In general, attention can be sustained for only a limited time, but breaks can refresh the ability to maintain attention over time.
Summary of Taxonomy of Attention
The variety of behavioral demands confronted by individuals in daily life is immense, and the functions of attention described above illustrate a view of attention as a complex and flexible system that can respond to this variety. To more fully understand the attention system, we must now look to the brain.
ATTENTION NETWORKS IN THE BRAIN
Unlike some other human behaviors whose function can be fairly specifically localized in the brain, there is no single brain area that is responsible for attention. Posner and colleagues have proposed a system of three brain networks that carry out different attention functions.37,38 Mesulam39 has also proposed an attentional matrix that has three components. These characterizations share many features with one another, and with the functional approach described above, but are not completely overlapping. Raz and Buhle40 have suggested that although this perceived inconsistency in terminology and definitions may be somewhat confusing or frustrating, it reflects a field that is grappling with the various aspects of attention and their role in other cognitive functions. Thus, for Raz and Buhle, this “terminological disarray” should lead clinicians and scientists to consider attention in terms of its multidimensional complexity and, in thinking this way, advance conceptual developments regarding the role of attention in behavior.
Posner's Attentional Networks
Based on behavioral and brain imaging studies, Posner and colleagues37,38 have proposed that the separate functions of attention are (1) alerting, (2) orienting, and (3) executive control. Alerting is the ability to stay focused in anticipation of an expected event, such as watching a red traffic light in anticipation of its turning green. If your attention falters, the driver behind you may let you know the light has turned green by honking! This alerting ability is subserved by the brain's thalamic, frontal, and parietal regions and is regulated by norepinephrine from the locus coeruleus.
The orienting function of attention allows the selection of one source of information for processing, among many possible sources. In a noisy restaurant, you are generally able to attend to your companion's conversation and not to the hustle and bustle around you. This orienting ability has been linked to superior parietal lobe, temporal parietal junction, and frontal eye fields of the brain and is thought to be modulated by cholinergic inputs from the basal forebrain.
Finally, executive control attention comes into play when more complex behavioral responses may be necessary, such as doing two things at once, performing a novel task, or assessing all aspects of a situation before making a response. In the early stages of learning a golf swing, there are many things to attend to and monitor in order to perform a successful swing. Brain areas active during executive control functions include the anterior cingulate cortex and lateral prefrontal cortex, moderated by dopamine.
Although there is evidence of the independence of the three attention networks described above, the proponents37,38 of this network model recognize that there are many tasks that may require the interaction of networks, and so the strict separation of functions may not be maintained in practice. However, the network model can be very useful in understanding the normal functioning of attention and also in predicting deficits in attentional function on the basis of information about location of brain damage. For example, damage to the norepinephrine projections to the cortex via the locus coeruleus will decrease an individual's ability to maintain alertness; he or she will likely be slow to respond or will miss important signals in the environment altogether. Damage to the temporal parietal junction, superior parietal lobe, or frontal eye fields will negatively affect the ability to selectively attend to relevant information in the face of distraction. Performance of people with this type of damage may be particularly impaired in noisy or busy environments. Damage to the anterior cingulate cortex or lateral prefrontal cortical region will produce impairments in self-monitoring of appropriate cognitive behaviors when confronted with a complex task. Performance of people with this type of damage may be most negatively affected when their task involves multiple steps or the processing of multiple sources of information. Thus, although the attention networks are not completely independent, knowing the area of brain damage may help in understanding a person's behavior in terms of attentional abilities.
Mesulam's Attentional Matrix
Another conceptualization of attention networks is given by Mesulam.39 His attentional matrix is made up of three components: (1) modality-specific processing, such as is carried out by primary sensory areas, (2) bottom-up attentional modulation from the ascending reticular activating system, and (3) top-down attentional modulation from prefrontal, parietal, and limbic areas of the brain. These three components interact with one another to control the focus of attention based on current needs and goals of the individual. This attention matrix is designed primarily to explain selective aspects of attention, similar to the orienting function described by Posner and colleagues above.
Mesulam39 described several studies to support his model component involving modality-specific attentional processing. For example, in a task where stimuli from three different modalities (eg, sight, sound, smell) are presented simultaneously but task performance requires attention to only one of the modalities, the primary sensory area in the brain for the attended modality shows greater activation than either of the other two sensory areas.41 Thus, attending to one sensory modality translates into increased activation in that sensory area of the brain. Another study reported a similar finding, but involved inhibition in the sensory areas associated with to-be-ignored stimuli, in addition to activation of the areas associated with the to-be-attended stimuli. In the study cited by Ghatan et al,42 participants performed a mental arithmetic task with distracting noise in the background. Measurements of brain activity showed decreased activation in the auditory association areas, indicating a suppression of auditory information processing. Together, these studies show that when the task allows it, brain processes supporting attention can occur even at very early sensory levels.
The second component of Mesulam's39 attentional matrix involves bottom-up control of arousal, or “attentional tone,” accomplished primarily through the ascending reticular activating system (ARAS). Attentional tone can be thought of as an index of the person's readiness to attend; low tone would characterize a drowsy state, whereas high tone would characterize an alert wakefulness. The ARAS includes pathways that Mesulam calls “domain independent” because their effects are not tied to any single sensory system. The two components of the ARAS are a reticulothalamocortical pathway and extrathalamic pathways involving several neurotransmitters (dopamine, serotonin, norepinephrine, acetylcholine, and gamma-aminobutyric acid). Studies have shown significant increases in ARAS activity as a person moves from being in an unfocused, relaxed state to a highly focused state of paying attention.43 In addition to this general influence on wakefulness or attentiveness, it is important to note that the ARAS is a complex system made up of a number of nuclei and pathways that may each affect attentional behaviors in different ways. Indeed Mesulam39 concluded that “components of the ARAS … collectively influence almost all aspects of attentional modulation in all parts of the cerebral cortex.”
The third and final component of Mesulam's proposed attentional matrix entails the top-down control of attention, primarily involving the frontal lobes of the brain but also including parietal and limbic areas. This component is domain independent, again operating regardless of the modality or form of incoming information. For example, Roland41 found that prefrontal areas were active in a selective attention task, regardless of the modality of information that was the focus of attention. Desimone44 has also shown the prefrontal activity is present in working memory tasks and may act to keep the contents of working memory from being lost due to distraction. Limbic areas such as the anterior cingulate are activated when tasks require divided or selective attention, regardless of the modality of the task. Parietal structures can modulate attention in light of motivational factors. For example, the posterior parietal cortex becomes very active when an animal is hungry and looking at food,45 indicating focused attention on the food. Together, these brain areas modulate the processing of incoming sensory information on the basis of motivational states and task goals, regardless of sensory modality.
Summary of Brain Models of Attention
Although different in their approach, both Mesulam's attentional matrix and Posner's attention networks involve almost every area of the brain in the functions of attention. None, however, is specialized for just that function. This distributed nature of attention in part contributes to the complexity of understanding its operation. It also helps make clear why almost any insult to the brain affects attentional functioning; both models provide useful heuristics for understanding the interplay between brain function and behavior.
Attention is a complex cognitive process that affects nearly everything we do. The approach to attention taken here was a functional one, reviewing attention in each of four modes of operation. Brain mechanisms were also discussed, with the aim of illustrating brain-behavior relationships. The overarching goal was to provide the reader with an overview of the workings of attention and a rubric for thinking about and understanding attentional behavior that would be useful in practice.
1. James W. The Principles of Psychology
. New York: Holt, 1890.
2. McAlonan K, Cavanaugh J, Wurtz RH. Attentional modulation of thalamic reticular neurons. J Neurosci
3. LaBerge D, Carlson RL, Williams JK, et al. Shifting attention in visual space: tests of moving-spotlight models versus an activity-distribution model. J Exp Psychol Hum Percept Perform
4. Stark ME, Grafman J, Fertig E. A restricted ‘spotlight' of attention in visual object recognition. Neuropsychologia
5. Vidyasagar TR. Gating of neuronal responses in macaque primary visual cortex by an attentional spotlight. Neuroreport
6. Kahneman D. Attention and Effort
. New York: Prentice Hall, 1973
7. Hellawell SJ, Brewin CR. A comparison of flashbacks and ordinary autobiographical memories of trauma: cognitive resources and behavioural observations. Behav Res Ther
8. Zohar D, Tzischinsky O, Epstein R, et al. The effects of sleep loss on medical residents' emotional reactions to work events: a cognitive-energy model. Sleep
. 2005;28:47–54. [Erratum in: Sleep
9. Navon D. Resources—a theoretical soupstone? Psychol Rev
10. Salthouse TA. Initiating the formalization of theories in cognitive aging. Psychol Aging
11. Jones S, Nyberg L, Sandblom J, et al. Cognitive and neural plasticity in aging: general and task-specific limitations. Neurosci Biobehav Rev
12. Mukherjee D, Levin RL, Heller W. The cognitive, emotional, and social sequelae of stroke: psychological and ethical concerns in post-stroke adaptation. Top Stroke Rehabil
13. Sarter M, Gehring WJ, Kozak R. More attention must be paid: the neurobiology of attentional effort. Brain Res Rev
14. Cole GG, Kentridge RW, Heywood CA. Object onset and parvocellular guidance of attentional allocation. Psychol Sci
15. Muhlenen A, Rempel MI, Enns JT. Unique temporal change is the key to attentional capture. Psychol Sci
16. Lepsien J, Nobre AC. Cognitive control of attention in the human brain: insights from orienting attention to mental representations. Brain Res
17. Farkas MS, Hoyer WJ. Processing consequences of perceptual grouping in selective attention. J Gerontol
18. Proulx MJ, Egeth HE. Target-nontarget similarity modulates stimulus-driven control in visual search. Psychonom Bull Rev
. 2006 13:524–529.
19. O'Connor KN, Sutter ML. Global spectral and location effects in auditory perceptual grouping. J Cogn Neurosci
20. Plude DJ, Hoyer WJ. Age and the selectivity of visual information processing. Psychol Aging
21. Degerman A, Rinne T, Salmi J, et al. Selective attention to sound location or pitch studied with fMRI. Brain Res
22. Connor CE, Egeth HE, Yantis S. Visual attention: bottom-up versus top-down. Curr Biol
23. Kok A. Varieties of inhibition: manifestations in cognition, event-related potentials and aging. Acta Psychol (Amst)
24. Wickens CD. Processing resources in attention. In: Parasuraman R, ed. Varieties of Attention
. New York: Academic Press, 1984:63–97.
25. Alais D, Morrone C, Burr D. Separate attentional resources for vision and audition. Proc Biol Sci
26. Sarno KJ, Wickens CD. Role of multiple resources in predicting time-sharing efficiency: evaluation of three workload models in a multiple-task setting. Int J Aviat Psychol
27. VanRullen R, Reddy L, Koch C. Visual search and dual tasks reveal two distinct attentional resources. J Cogn Neurosci
28. Lien MC, Proctor RW, Ruthroff E. Still no evidence for perfect timesharing with two ideomotor-compatible tasks: a reply to Greenwald (2003). J Exp Psychol Hum Percept Perform
29. Ruthruff E, Hazeltine E, Remington RW. What causes residual dual-task interference after practice? Psychol Res
30. Gopher D. Attention control: explorations of the work of an executive controller. Brain Res Cogn Brain Res
31. Lorenz B, Kuritz-Kaiser A, Schmerwitz S, et al. Improving spatial awareness in the aircraft cockpit: partially supporting evidence for the concept of scene-linking. Cogn Process
. 2006;5(7 Suppl):149.
32. Dreisbach G, Haider H. Preparatory adjustment of cognitive control in the task switching paradigm. Psychon Bull Rev
33. Rubin O, Koch I. Exogenous influences on task set activation in task switching. Q J Exp Psychol (Colchester)
34. Yeung N, Nystrom LE, Aronson JA, et al. Between-task competition and cognitive control in task switching. J Neurosci
35. Oken BS, Salinsky MC, Elsas SM. Vigilance, alertness, or sustained attention: physiological basis and measurement. Clin Neurophysiol
36. Mouloua M, Parasuraman R. Aging and cognitive vigilance: effects of spatial uncertainty and event rate. Exp Aging Res
37. Fan J, Posner M. Human attentional networks. Psychiatr Prax
38. Fan J, McCandliss BD, Posella J, et al. The activation of attentional networks. Neuroimage
39. Mesulam MM. Principles of Behavioral and Cognitive Neurology
. New York: Oxford University Press, 2000.
40. Raz A, Buhle J. Typologies of attentional networks. Nat Rev Neurosci
41. Roland PE. Cortical regulation of selective attention in man. J Neurophysiol
42. Ghatan PH, Hsieh JC, Petersson KM, et al. Coexistence of attention-based facilitation and inhibition in the human cortex. Neuroimage
43. Kinomura S, Larsson J, Gulyas B, et al. Activation by attention of the human reticular formation and thalamic intralaminar nuclei. Science
44. Desimone R. Neural mechanisms for visual memory and their role in attention. Proc Natl Acad Sci U S A
45. Lynch JC. The functional organization of posterior parietal association cortex. Behav Brain Sci